def test_should_get_distance_return_the_correct_values_if_there_are_no_gaps(self):
matrix = Blosum62()
self.assertEqual(-1, matrix.get_distance('A', 'R'))
self.assertEqual(-3, matrix.get_distance('N', 'F'))
self.assertEqual(-2, matrix.get_distance('X', 'C'))
self.assertEqual(+4, matrix.get_distance('I', 'I'))
self.assertEqual(+4, matrix.get_distance('V', 'V'))
def test_most_frequent_A_with_BLOSUM62(self):
# setup
sequences = MSA(['AA', 'AC', 'AC'])
# results
result = Star(sequences, Blosum62()).compute()
expected = 30
# check
self.assertEqual(expected, result)
def test_only_gaps_with_BLOSUM62(self):
# setup
sequences = MSA(['---', '---'])
# results
result = SumOfPairs(sequences, Blosum62()).compute()
expected = 3
# check
self.assertEqual(expected, result)
def test_basic_score_with_gaps_BLOSUM62(self):
# setup
sequences = MSA(['FA', 'A-'])
# results
result = SumOfPairs(sequences, Blosum62()).compute()
expected = -10
# check
self.assertEqual(expected, result)
def run_all_scores(msa: list) -> None:
align_sequences = list(pair[1] for pair in msa)
sequences_id = list(pair[0] for pair in msa)
# Percentage of non-gaps and totally conserved columns
non_gaps = PercentageOfNonGaps()
totally_conserved_columns = PercentageOfTotallyConservedColumns()
percentage = non_gaps.compute(align_sequences)
conserved = totally_conserved_columns.compute(align_sequences)
print("Percentage of non-gaps: {0} %".format(percentage))
print("Percentage of totally conserved columns: {0}".format(conserved))
# Entropy
value = Entropy().compute(align_sequences=align_sequences)
print("Entropy score: {0}".format(value))
# Sum of pairs
value = SumOfPairs(Blosum62()).compute(align_sequences=align_sequences)
print("SumOfPairs score (Blosum62): {0}".format(value))
value = SumOfPairs(PAM250()).compute(align_sequences=align_sequences)
print("SumOfPairs score (PAM250): {0}".format(value))
value = SumOfPairs(FileMatrix('PAM380.txt')).compute(align_sequences=align_sequences)
print("SumOfPairs score (PAM380): {0}".format(value))
# Star
value = Star(Blosum62()).compute(align_sequences=align_sequences)
print("Star score (Blosum62): {0}".format(value))
value = Star(PAM250()).compute(align_sequences=align_sequences)
print("Star score (PAM250): {0}".format(value))
# STRIKE
value = Strike().compute(align_sequences=align_sequences,
sequences_id=sequences_id,
chains=['A', 'E', 'A', 'A'])
print("STRIKE score: {0}".format(value))
def test_should_get_distance_return_the_gap_penalty_if_a_char_is_a_gap(self):
matrix = Blosum62()
self.assertEqual(matrix.gap_penalty, matrix.get_distance('A', '-'))
self.assertEqual(matrix.gap_penalty, matrix.get_distance('-', 'B'))
def test_should_constructor__modify_the_gap_penalty(self):
matrix = Blosum62(-10)
self.assertEqual(-10, matrix.gap_penalty)
def test_should_default_gap_penalty_be_minus_eight(self):
matrix = Blosum62()
self.assertEqual(-8, matrix.gap_penalty)
def test_should_get_distance_throw_an_exception_if_a_char_is_invalid(self):
matrix = Blosum62()
with self.assertRaises(Exception):
matrix.get_distance('J', 'A')
def test_should_get_distance_return_one_if_the_two_chars_are_gaps(self):
matrix = Blosum62()
self.assertEqual(1, matrix.get_distance('-', '-'))
def setUp(self):
self.sumofpairs_PAM250 = SumOfPairs(PAM250())
self.sumofpairs_Blosum62 = SumOfPairs(Blosum62())
def setUp(self):
self.star_PAM250 = Star(PAM250())
self.star_Blosum62 = Star(Blosum62())